Openl3 0.4.0 - Support for Tensorflow 2

[beasteers]

Figured I would push this out while I'm waiting for something else to build.

Related PR containing updated models: https://github.com/marl/openl3/pull/61

Setup Changes

• Openl3 now requires tensorflow>=2.0.0 and installs it by default (there is no longer a separate GPU package)
• Now requires kapre>=0.3.5 - TODO: make sure we have the exact minimum kapre version - I remember checking git blame, but haven't tested anything
• keras as a standalone package was removed from dependencies (we're using tf.keras)
• travis.yml: removed python 2.7 & 3.5 and added 3.7 & 3.8 since tensorflow only supports 3.6-3.8
  • needed to install Cython first for python 3.8 in order to install skimage (RuntimeError: Cython >= 0.23.4 is required to build scikit-image from git checkout)

Doc Changes

• Changed tensorflow dependency message to reflect updates
• Added "Choosing an Audio Frontend (CPU / GPU)" section to tutorial.rst

Code Changes

• core.py
  • added params: get_audio_embedding(frontend='auto'), process_audio_file(frontend='auto'), process_video_file(audio_frontend='auto')
  • Added function preprocess_audio(y, sr, input_repr=None) that encapsulates the librosa frontend (as well as preprocessing for the kapre frontend)
    • for librosa, you pass the input_repr and for kapre inputs, you leave input_repr=None
• cli.py - added cli flag (--audio-frontend)
• models.py
  • added param load_audio_embedding_model(frontend='kapre')
  • using new kapre composite layer helpers get_stft_magnitude_layer
  • disabled latest mag2db code and patched in the legacy version (kapre_v0_1_4_magnitude_to_decibel)
  • kapre is now technically an optional dependency (will only try to import if we try to load a model with kapre frontend)
    • we still install it with setup.py, but if someone wanted to, they could install everything manually without kapre and openl3 should still work for the librosa frontend

Test Changes

• we now have separate regression data for kapre/librosa
• added tests for frontend model following the existing model tests
• converted some tests to use pytest.mark.parameterize to avoid doubling the length of the tests for testing frontends

Dev Util Changes

• added tests/generate_regression.py which generates new regression data
• added tests/package_weights.py which takes the weights files in the openl3 package folder and gzips them for git push
• added tests/migration/remove_layers.py which lets us strip out the spectrogram (or any other) layers
• tests/migration/ has a few other analysis things/notebooks that were used early on in the frontend testing

Before merging:

• double check dependency versions
• are the pinned versions still valid? might need some help with this one
• Change models download url in setup.py to main repo (currently it's pointing at my fork so I could test with travis)
• should we integrate changes from https://github.com/marl/openl3/pull/55?
• should we run the classifier comparison one more time right before merging as a safety check? idk

[beasteers]

@justinsalamon I don't have permissions to merge either of them so imma need u to merge the models first ;p

[justinsalamon]

doh! on it

[justinsalamon]

@beasteers model merged!

[beasteers]

@justinsalamon this looks all good too! whenever you're ready I think we're good to merge.